G. Leonardi

Open source deep learning models for accurate fastener defect inspection

The present work investigates the possibility of adopting open source DL models, specifically Transformer-based architectures and Convolutional Neural Networks, to classify fastener component images into defective or non-defective, and to segment defective ones, in order to enhance detection localization and to support...